Overnight information and intraday trading behavior ...

Journal of Multinational Financial Management

10 (2000) 495 ? 509

locate/econbase

Overnight information and intraday trading behavior: evidence from NYSE cross-listed stocks and their local market information

Kalok Chan a, Mark Chockalingam b, Kent W.L. Lai c,*

a Department of Finance, Hong Kong Uni6ersity of Science and Technology, Hong Kong b Schering-Plough Health Care, Memphis, TN, USA

c Department of Accounting and Finance, Lingnan Uni6ersity, Tuen Mun, N.T. Hong Kong

Received 15 July 1999; accepted 4 March 2000

Abstract

In this paper we study how overnight price movements in local markets affect the trading activity of foreign stocks on the NYSE. We find that local price movements affect not only the opening returns of foreign stocks, but also their returns in the first 30-min interval. The magnitude of local price movements is positively related to price volatility of foreign stocks, and this relation is stronger at the NYSE open and weaker afterward. This result helps explain why intraday price volatility is high at the open and lower at midday. However, local price movements cannot account for intraday variations in trading volume. We also find that trading volume for foreign stocks is strongly correlated with NYSE opening price volatility and weakly correlated with local market overnight price volatility. We interpret the result as evidence that the trading activity of foreign stocks on the NYSE is related more to liquidity trading of US investors and less to local market information. ? 2000 Elsevier Science B.V. All rights reserved.

JEL classification: G14 Information and Market Efficiency; G15 International Financial Markets

Keywords: Intraday volatility; Market microstructure; Multiple-market trading

* Corresponding author. Tel.: + 852-26168166; fax: +852-24664751. E-mail address: kwlai@ln.edu.hk (K.W.L. Lai).

1042-444X/00/$ - see front matter ? 2000 Elsevier Science B.V. All rights reserved. PII: S 1 0 4 2 - 4 4 4 X ( 0 0 ) 0 0 0 3 0 - X

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1. Introduction

Extensive empirical evidence documents that the stock market is more active at the beginning of the trading session. Measures of market activity, such as trading volume, price volatility, and number of transactions, are higher at the open and close for NYSE stocks (Jain and Joh (1988), Foster and Viswanathan (1993), and Jang and Lee (1993)). Several studies conjecture that the higher market activity at the open is due to overnight information that accumulates during the NYSE nontrading period. For example, Berry and Howe (1994) document that the number of news announcements released by Reuter's News Service increases at 8:00 am (EST) -- one and a half hours before the NYSE open--indicating an increase in public information flow before the open. Foster and Viswanathan (1993) show that informed traders who gather private information during the nontrading period trade more aggressively after the open if they suspect their information will become public soon. Brock and Kleidon (1992) and Gerety and Mulherin (1992) argue that because of the new information that arrives during the nontrading period, the portfolio that is optimal during the previous close will no longer be optimal when the market reopens. Therefore, market activity increases immediately after the open as investors rebalance their portfolios.

In light of the relation between market activity and information flow, many authors examine internationally cross-listed stocks and check whether their price behavior is different from that of non-cross-listed stocks, given their different information-flow patterns (Barclay et al., 1990; Kleidon and Werner, 1993; Chan et al., 1994; Choe, 1994; Foster and George, 1994). Despite the intuitive appeal that the trading behavior of these cross-listed stocks in the morning is related to overnight information released in their local markets, none of these studies directly tests this possibility.

In this paper we examine the intraday patterns of trading volume and price volatility for stocks traded on the NYSE and listed on Asia-Pacific and UK exchanges. We test whether these patterns are related to public information accumulated overnight. Unlike Berry and Howe (1994) who use the number of news articles released during the nontrading period, or other researchers who use close-to-open return volatility, we infer the overnight information flow of these cross-listed stocks directly from price movements in their local markets. Since most information generated during the NYSE nontrading period about these foreign stocks is reflected in local markets, local stock price movement is a good proxy for overnight information. If the market activity at the open is related to overnight information, we expect to find a positive relation between the level of market activity in the morning and the magnitude of local stock price movement.

Furthermore, as information about these foreign stocks (both public and private) is more likely to arrive during the NYSE overnight period than during the trading period, market activity is greater in the morning than the mid-day. This suggests that once we control for the effect of overnight information (local stock price movements), intraday variations in market activity will be reduced.

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Unlike previous studies, we infer overnight information from the local price movement rather than from the NYSE opening returns. Although the local price movement and NYSE opening returns are closely related, they are not perfectly correlated, as the price in one market could move because of the trading activity there. Furthermore, local trading sessions for Asia-Pacific stocks are closed before the NYSE opens. Therefore, we examine how local price movements, which are public information to US investors, affect the trading activity of foreign stocks on US exchanges.

We find that overnight price movements in local markets affect not only opening returns of foreign stocks, but also returns during the first 30 minutes. Also, the magnitude of local price movements is positively related to the price movement of foreign stocks in the morning. The relation is stronger around the open and weaker afterward. This diminishing effect of overnight information on intraday price movements helps explain why price volatility is higher at the open and lower at midday. On the other hand, local price movements cannot explain intraday variations in trading volume. This suggests that the trading volume of foreign stocks on the NYSE is not related to overnight public information. We also find that trading volume is strongly correlated with NYSE opening price movement and weakly correlated with local market price movement. We interpret this result as evidence that the trading activity of foreign stocks on the NYSE is related more to liquidity trading of US investors and less to local market information.

The paper proceeds as follows. Section 2 discusses the relation between overnight information and intraday market activity. Section 3 describes the data and summary statistics. Section 4 presents empirical methodologies and results. Section 5 presents the conclusion.

2. Relation between overnight information and intraday market activity

2.1. Why market acti6ity is higher at the open

Extensive empirical evidence documents that stock market behavior at the beginning of the NYSE trading session differs from the rest of the day. Wood et al. (1985), Harris (1986), and Lockwood and Linn (1990) examine intraday stock returns and find that price volatility is higher near the open and close of the trading session. Jain and Joh (1988), Foster and Viswanathan (1993), and Jang and Lee (1993) find that trading volume and number of transactions are also higher at the open. Several explanations may account for this trading behavior. First, much public information accumulates overnight and is not reflected in prices during the NYSE nontrading period. Once the NYSE opens, overnight information is quickly incorporated into prices, resulting in a large price movement at the open. Berry and Howe (1994) and Mitchell and Mulherin (1994) examine the effect of public information on market activity. Using the number of news announcements released by Reuter's News Service as a measure of public information flow, Berry and Howe (1994) document that information flow substantially increases at 8:00 am (EST).

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Second, informed traders gather private information during the nontrading period and may act strategically when trading with liquidity traders. This is analogous to the interday trading strategies analyzed in Foster and Viswanathan (1990). In their model, the informed trader receives private information at the beginning of the week. Since a portion of the private information is made public each day, the information becomes less valuable through time. The informed trader, knowing a public signal is forthcoming, trades more aggressively so that more information is reflected through trading. A similar logic can be applied to intraday trading. If informed traders receive private information overnight and suspect the information may be leaked later in the day, they will trade immediately after the open.

Third, volume at the close and open reflects trades made to rebalance portfolios before and after the overnight trading halt. Brock and Kleidon (1992) argue that because of overnight information, portfolios that are optimal during the previous close will no longer be optimal when the market reopens. Furthermore, portfolios that are optimal at the close can differ, because of the imminent nontrading period, from portfolios that are optimal during the continuous trading period. This inelastic demand to trade induces a surge in trading activity at the open and close.

Fourth, since the NYSE operates continuously during the trading day, but commences trading with a call auction, these two trading mechanisms could generate different transitory volatilities. Amihud and Mendelson (1987) and Stoll and Whaley (1990) document that open-to-open return variances are greater than close-to-close return variances for stocks traded on the NYSE. This implies that opening prices contain larger pricing errors than closing prices. However, subsequent studies (e.g., Amihud and Mendelson, 1991; Choe and Shin, 1993; Masulis and Ng, 1995) find similar evidence for stocks traded on other exchanges that have different trading mechanisms. This suggests that higher transitory volatility at the open is in fact due to the overnight trading halt. Without trading venues, the overnight trading halt disturbs the process of price formation until the open (Grundy and McNichols, 1989; Dow and Gorton, 1993; Leach and Madhavan, 1993). Gerety and Mulherin (1994) find that transitory volatility declines during the trading day both for the Dow Jones 65 Composite price index and for individual firms in the Dow Jones 30 index.

2.2. A simple regression framework for understanding the effect of o6ernight information

As discussed above, one reason for increased market activity at the open is that overnight information accumulates during the NYSE nontrading period. This is true even when the overnight information becomes public, since investors experience uncertainty in interpreting the information. Furthermore, as several researchers (Grundy and McNichols, 1989; Dow and Gorton, 1993; Leach and Madhavan, 1993) argue, multiple rounds of trading can produce prices that are less noisy and reveal more information than a single round of trading. Therefore, overnight information affects market activity at the open, but the effect diminishes

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during the day. The diminishing effect of overnight information might explain why the market activity surges at the open and declines afterward. This can be illustrated by a simple regression model. Suppose V~,t denotes intraday market activity (either trading volume or price movement) for interval ~ at day t, and Ft denotes overnight information. If the effect of overnight information on market activity diminishes during the day, then in a set of regression equations for different intervals:

V~,t = h~ + i~ Ft + ~,t

(1)

the i~ coefficient is larger for smaller ~. Since the average of V~,t is given by

V( ~ = h~ + i~F(

(2)

V( ~ could be higher for earlier intervals (smaller ~), even though the h~'s are the same across all intervals. Equation (2) also suggests that if intraday variations in

V~,t are only due to innovations in overnight information, the h~ intercepts will have no variations once Ft is allowed to affect V~,t differently at different intervals. Note that the regression models assume that variations in market activity are solely

caused by overnight information. This can be justified, especially for foreign stocks

that have much information released in local markets overnight. If other variables

contribute to intraday variations in market activity, the h~ intercept will not be the same even after controlling for Ft.

3. Data and summary statistics

We obtain data from the NYSE Trades and Quotes (TAQ) database. It comprises all trade records and quotation records on the NYSE, AMEX, and regional exchanges. The trade records contain the time to the nearest second, date, ticker symbol, price, and number of shares traded; the quotation records contain the time, date, ticker symbol, bid and ask price, and number of shares the specialist quotes for the bid and the ask. We also obtain data from the EXTEL database, which comprises daily price records for most of the firms in the United Kingdom and large firms worldwide. The prices are in terms of foreign currencies, and are not translated into the US dollars. Therefore, the relationship between the price movement in the US and foreign market is not due to exchange rate fluctuation.

The sample period is the first quarter of 1993. Since we are examining the effect of overnight local information on NYSE trading activity, we select foreign stocks whose local trading sessions precede the NYSE. To be included in the analysis, the foreign stocks must be listed on the NYSE and have at least 20 days of more than 10 quotes a day. Each day, we match the transactions data for foreign stocks with daily stock prices in local markets. For several foreign stocks that do not have local stock prices available from EXTEL, we obtain the local data from the New York Times. Among the 29 European stocks that meet the requirements, 21 are UK. For convenience, we exclude non-UK European stocks so that the length of overlapping trading hours on the NYSE and local exchanges is the same for European stocks. Seven Asia-Pacific stocks meet our selection requirements.

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